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Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia
Author(s) -
Ribic Bojan,
Pezo Lato,
Sincic Dinko,
Loncar Biljana,
Voca Neven
Publication year - 2019
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.4632
Subject(s) - european union , legislation , estimation , municipal solid waste , engineering , sustainable management , artificial neural network , environmental planning , environmental economics , business , sustainability , waste management , environmental science , computer science , artificial intelligence , economics , ecology , systems engineering , biology , political science , law , economic policy
Summary The European Union's environmental legislation related to environmental protection, already implemented in the national legislation of the Republic of Croatia, aims to introduce a system of integrated and sustainable waste management. Within such a system, it is of utmost importance to have a better estimate of the amount of municipal waste generated, which directly influences future planning in the waste management sector. The aim of this research was to develop and optimize models for the estimation of generated municipal waste by application of methodology using neural network models, and taking into account the socio‐economic impact as well as the inputs regarding the actual waste management trends. In this paper, an artificial neural network models were used to predict the municipal waste generation in Zagreb, Croatia. The standardized socio‐economic and waste management variables were chosen to encompass 2013 to 2016 period. Moreover, the test prediction of the observed data was performed for 2017. Developed models sufficiently predicted the quantities of different municipal waste fractions and in that sense can contribute to better planning of upcoming waste management systems that will be sustainable and in order to meet the European Union commitments.